platform engineer infrastructure

CloudLinux builds Linux infrastructure and security products. Its Infrastructure Department runs an observability platform, GitLab and CI runners, engineering services, and automation for provisioning and configuration.

• Run the observability platform, onboard teams, monitor cost and capacity, and maintain alerting;
• Run GitLab and the CI runner fleet, including upgrades, capacity, access, backups, and restore drills;
• Keep services healthy with production monitoring and runbooks;
• Deploy new services from scratch as code, with monitoring, backups, and documentation;
• Handle developers' access, onboarding, pipeline, exporter, and dashboard requests, turning recurring requests into self-service;
• Run incidents, diagnose and mitigate impact, restore services, complete root-cause analyses and post-mortems, and deliver prevention or detection improvements;
• Ship changes as code through reviewed merge requests and plan and check every change;
• Write runbooks, onboarding guides, maintenance notices, and status updates for engineers outside the team;
• Work with AI agents by delegating collection and drafting, reviewing outputs, and recording learnings.

• Senior-level experience in infrastructure, platform, or site reliability engineering, including responsibility for keeping at least one production service running;
• Linux systems administration and debugging on bare metal and virtual machines;
• Production Kubernetes delivered through GitOps, including independently performed cluster upgrades;
• Infrastructure as code using Ansible and Terraform or OpenTofu, with changes reviewed in merge requests;
• Production GitLab administration and GitLab CI, or equivalent depth with another CI system;
• Working knowledge of Prometheus and Grafana, including operating them for a team, writing alert rules and dashboards, and reading PromQL;
• Ability to write technical explanations, runbooks, notices, and answers for engineers outside the team;
• Strong communication and interpersonal skills for scoping, prioritizing, coordinating, and communicating work with product teams;
• Advanced use of AI engineering assistants such as Claude and Codex, including context provision, task decomposition, agent-loop design, delegated execution, debugging, testing, and verification;
• Upper-intermediate or higher English for clear team communication;
• Nice to have: alerting design with SLOs and burn-rate alerts, microVM isolation for CI, S3-compatible object storage operations, AWS cost work, self-hosted Sentry or another Kafka-, ClickHouse-, and Redis-backed application operated under load, Python or Go for exporters and small internal services.

• Fully remote work with flexible working hours from any location worldwide;
• Professional development focus;
• Interesting and challenging projects;
• 24 Paid vacation days per year, 10 national holidays, and unlimited sick leave;
• Private medical insurance compensation;
• Co-working and gym/sports reimbursement;
• Education budget;
• Opportunity to receive a reward for an innovative idea that the company can patent.